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<div class="title">ShapeDatasets.h</div>  </div>
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<a href="_shape_datasets_8h.xhtml">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno">    1</span>&#160;<span class="comment">/*</span></div>
<div class="line"><a name="l00002"></a><span class="lineno">    2</span>&#160;<span class="comment"> * Copyright (c) 2017 ARM Limited.</span></div>
<div class="line"><a name="l00003"></a><span class="lineno">    3</span>&#160;<span class="comment"> *</span></div>
<div class="line"><a name="l00004"></a><span class="lineno">    4</span>&#160;<span class="comment"> * SPDX-License-Identifier: MIT</span></div>
<div class="line"><a name="l00005"></a><span class="lineno">    5</span>&#160;<span class="comment"> *</span></div>
<div class="line"><a name="l00006"></a><span class="lineno">    6</span>&#160;<span class="comment"> * Permission is hereby granted, free of charge, to any person obtaining a copy</span></div>
<div class="line"><a name="l00007"></a><span class="lineno">    7</span>&#160;<span class="comment"> * of this software and associated documentation files (the &quot;Software&quot;), to</span></div>
<div class="line"><a name="l00008"></a><span class="lineno">    8</span>&#160;<span class="comment"> * deal in the Software without restriction, including without limitation the</span></div>
<div class="line"><a name="l00009"></a><span class="lineno">    9</span>&#160;<span class="comment"> * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or</span></div>
<div class="line"><a name="l00010"></a><span class="lineno">   10</span>&#160;<span class="comment"> * sell copies of the Software, and to permit persons to whom the Software is</span></div>
<div class="line"><a name="l00011"></a><span class="lineno">   11</span>&#160;<span class="comment"> * furnished to do so, subject to the following conditions:</span></div>
<div class="line"><a name="l00012"></a><span class="lineno">   12</span>&#160;<span class="comment"> *</span></div>
<div class="line"><a name="l00013"></a><span class="lineno">   13</span>&#160;<span class="comment"> * The above copyright notice and this permission notice shall be included in all</span></div>
<div class="line"><a name="l00014"></a><span class="lineno">   14</span>&#160;<span class="comment"> * copies or substantial portions of the Software.</span></div>
<div class="line"><a name="l00015"></a><span class="lineno">   15</span>&#160;<span class="comment"> *</span></div>
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<div class="line"><a name="l00017"></a><span class="lineno">   17</span>&#160;<span class="comment"> * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,</span></div>
<div class="line"><a name="l00018"></a><span class="lineno">   18</span>&#160;<span class="comment"> * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE</span></div>
<div class="line"><a name="l00019"></a><span class="lineno">   19</span>&#160;<span class="comment"> * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER</span></div>
<div class="line"><a name="l00020"></a><span class="lineno">   20</span>&#160;<span class="comment"> * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,</span></div>
<div class="line"><a name="l00021"></a><span class="lineno">   21</span>&#160;<span class="comment"> * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE</span></div>
<div class="line"><a name="l00022"></a><span class="lineno">   22</span>&#160;<span class="comment"> * SOFTWARE.</span></div>
<div class="line"><a name="l00023"></a><span class="lineno">   23</span>&#160;<span class="comment"> */</span></div>
<div class="line"><a name="l00024"></a><span class="lineno">   24</span>&#160;<span class="preprocessor">#ifndef __ARM_COMPUTE_TEST_SHAPE_DATASETS_H__</span></div>
<div class="line"><a name="l00025"></a><span class="lineno">   25</span>&#160;<span class="preprocessor"></span><span class="preprocessor">#define __ARM_COMPUTE_TEST_SHAPE_DATASETS_H__</span></div>
<div class="line"><a name="l00026"></a><span class="lineno">   26</span>&#160;<span class="preprocessor"></span></div>
<div class="line"><a name="l00027"></a><span class="lineno">   27</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="_tensor_shape_8h.xhtml">arm_compute/core/TensorShape.h</a>&quot;</span></div>
<div class="line"><a name="l00028"></a><span class="lineno">   28</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="_datasets_8h.xhtml">tests/framework/datasets/Datasets.h</a>&quot;</span></div>
<div class="line"><a name="l00029"></a><span class="lineno">   29</span>&#160;</div>
<div class="line"><a name="l00030"></a><span class="lineno">   30</span>&#160;<span class="preprocessor">#include &lt;type_traits&gt;</span></div>
<div class="line"><a name="l00031"></a><span class="lineno">   31</span>&#160;</div>
<div class="line"><a name="l00032"></a><span class="lineno">   32</span>&#160;<span class="keyword">namespace </span>arm_compute</div>
<div class="line"><a name="l00033"></a><span class="lineno">   33</span>&#160;{</div>
<div class="line"><a name="l00034"></a><span class="lineno">   34</span>&#160;<span class="keyword">namespace </span>test</div>
<div class="line"><a name="l00035"></a><span class="lineno">   35</span>&#160;{</div>
<div class="line"><a name="l00036"></a><span class="lineno">   36</span>&#160;<span class="keyword">namespace </span>datasets</div>
<div class="line"><a name="l00037"></a><span class="lineno">   37</span>&#160;{</div>
<div class="line"><a name="l00039"></a><span class="lineno"><a class="line" href="classarm__compute_1_1test_1_1datasets_1_1_small1_d_shape.xhtml">   39</a></span>&#160;<span class="keyword">class </span><a class="code" href="classarm__compute_1_1test_1_1datasets_1_1_small1_d_shape.xhtml">Small1DShape</a> final : <span class="keyword">public</span> <a class="code" href="classarm__compute_1_1test_1_1framework_1_1dataset_1_1_singleton_dataset.xhtml">framework::dataset::SingletonDataset</a>&lt;TensorShape&gt;</div>
<div class="line"><a name="l00040"></a><span class="lineno">   40</span>&#160;{</div>
<div class="line"><a name="l00041"></a><span class="lineno">   41</span>&#160;<span class="keyword">public</span>:</div>
<div class="line"><a name="l00042"></a><span class="lineno"><a class="line" href="classarm__compute_1_1test_1_1datasets_1_1_small1_d_shape.xhtml#a42e48f27686347e905050153e3e87dc5">   42</a></span>&#160;    <a class="code" href="classarm__compute_1_1test_1_1datasets_1_1_small1_d_shape.xhtml#a42e48f27686347e905050153e3e87dc5">Small1DShape</a>()</div>
<div class="line"><a name="l00043"></a><span class="lineno">   43</span>&#160;        : <a class="code" href="classarm__compute_1_1test_1_1framework_1_1dataset_1_1_singleton_dataset.xhtml#ad23d34842f593ae646353d39fc0466cd">SingletonDataset</a>(<span class="stringliteral">&quot;Shape&quot;</span>, <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>{ 256<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a> })</div>
<div class="line"><a name="l00044"></a><span class="lineno">   44</span>&#160;    {</div>
<div class="line"><a name="l00045"></a><span class="lineno">   45</span>&#160;    }</div>
<div class="line"><a name="l00046"></a><span class="lineno">   46</span>&#160;};</div>
<div class="line"><a name="l00047"></a><span class="lineno">   47</span>&#160;</div>
<div class="line"><a name="l00049"></a><span class="lineno"><a class="line" href="namespacearm__compute_1_1test_1_1datasets.xhtml#ae6b0d1adb193102aad304e0765655a3a">   49</a></span>&#160;<span class="keyword">using</span> <a class="code" href="classarm__compute_1_1test_1_1framework_1_1dataset_1_1_container_dataset.xhtml">ShapeDataset</a> = <a class="code" href="classarm__compute_1_1test_1_1framework_1_1dataset_1_1_container_dataset.xhtml">framework::dataset::ContainerDataset&lt;std::vector&lt;TensorShape&gt;</a>&gt;;</div>
<div class="line"><a name="l00050"></a><span class="lineno">   50</span>&#160;</div>
<div class="line"><a name="l00052"></a><span class="lineno"><a class="line" href="classarm__compute_1_1test_1_1datasets_1_1_small2_d_shapes.xhtml">   52</a></span>&#160;<span class="keyword">class </span><a class="code" href="classarm__compute_1_1test_1_1datasets_1_1_small2_d_shapes.xhtml">Small2DShapes</a> final : <span class="keyword">public</span> <a class="code" href="classarm__compute_1_1test_1_1framework_1_1dataset_1_1_container_dataset.xhtml">ShapeDataset</a></div>
<div class="line"><a name="l00053"></a><span class="lineno">   53</span>&#160;{</div>
<div class="line"><a name="l00054"></a><span class="lineno">   54</span>&#160;<span class="keyword">public</span>:</div>
<div class="line"><a name="l00055"></a><span class="lineno"><a class="line" href="classarm__compute_1_1test_1_1datasets_1_1_small2_d_shapes.xhtml#af5e1a4f2a8c5ec30856fbe4f3efe4ee9">   55</a></span>&#160;    <a class="code" href="classarm__compute_1_1test_1_1datasets_1_1_small2_d_shapes.xhtml#af5e1a4f2a8c5ec30856fbe4f3efe4ee9">Small2DShapes</a>()</div>
<div class="line"><a name="l00056"></a><span class="lineno">   56</span>&#160;        : <a class="code" href="classarm__compute_1_1test_1_1framework_1_1dataset_1_1_container_dataset.xhtml">ShapeDataset</a>(<span class="stringliteral">&quot;Shape&quot;</span>,</div>
<div class="line"><a name="l00057"></a><span class="lineno">   57</span>&#160;    {</div>
<div class="line"><a name="l00058"></a><span class="lineno">   58</span>&#160;        <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>{ 7<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 7<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a> },</div>
<div class="line"><a name="l00059"></a><span class="lineno">   59</span>&#160;                     <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>{ 27<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 13<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a> },</div>
<div class="line"><a name="l00060"></a><span class="lineno">   60</span>&#160;                     <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>{ 128<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 64<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a> }</div>
<div class="line"><a name="l00061"></a><span class="lineno">   61</span>&#160;    })</div>
<div class="line"><a name="l00062"></a><span class="lineno">   62</span>&#160;    {</div>
<div class="line"><a name="l00063"></a><span class="lineno">   63</span>&#160;    }</div>
<div class="line"><a name="l00064"></a><span class="lineno">   64</span>&#160;};</div>
<div class="line"><a name="l00065"></a><span class="lineno">   65</span>&#160;</div>
<div class="line"><a name="l00067"></a><span class="lineno"><a class="line" href="classarm__compute_1_1test_1_1datasets_1_1_small3_d_shapes.xhtml">   67</a></span>&#160;<span class="keyword">class </span><a class="code" href="classarm__compute_1_1test_1_1datasets_1_1_small3_d_shapes.xhtml">Small3DShapes</a> final : <span class="keyword">public</span> <a class="code" href="classarm__compute_1_1test_1_1framework_1_1dataset_1_1_container_dataset.xhtml">ShapeDataset</a></div>
<div class="line"><a name="l00068"></a><span class="lineno">   68</span>&#160;{</div>
<div class="line"><a name="l00069"></a><span class="lineno">   69</span>&#160;<span class="keyword">public</span>:</div>
<div class="line"><a name="l00070"></a><span class="lineno"><a class="line" href="classarm__compute_1_1test_1_1datasets_1_1_small3_d_shapes.xhtml#a231cfeceb3e607c02a8347adeb894eb9">   70</a></span>&#160;    <a class="code" href="classarm__compute_1_1test_1_1datasets_1_1_small3_d_shapes.xhtml#a231cfeceb3e607c02a8347adeb894eb9">Small3DShapes</a>()</div>
<div class="line"><a name="l00071"></a><span class="lineno">   71</span>&#160;        : <a class="code" href="classarm__compute_1_1test_1_1framework_1_1dataset_1_1_container_dataset.xhtml">ShapeDataset</a>(<span class="stringliteral">&quot;Shape&quot;</span>,</div>
<div class="line"><a name="l00072"></a><span class="lineno">   72</span>&#160;    {</div>
<div class="line"><a name="l00073"></a><span class="lineno">   73</span>&#160;        <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>{ 7<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 7<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 5U },</div>
<div class="line"><a name="l00074"></a><span class="lineno">   74</span>&#160;                     <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>{ 27<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 13<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 37U },</div>
<div class="line"><a name="l00075"></a><span class="lineno">   75</span>&#160;                     <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>{ 128<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 64<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 21U }</div>
<div class="line"><a name="l00076"></a><span class="lineno">   76</span>&#160;    })</div>
<div class="line"><a name="l00077"></a><span class="lineno">   77</span>&#160;    {</div>
<div class="line"><a name="l00078"></a><span class="lineno">   78</span>&#160;    }</div>
<div class="line"><a name="l00079"></a><span class="lineno">   79</span>&#160;};</div>
<div class="line"><a name="l00080"></a><span class="lineno">   80</span>&#160;</div>
<div class="line"><a name="l00082"></a><span class="lineno"><a class="line" href="classarm__compute_1_1test_1_1datasets_1_1_small4_d_shapes.xhtml">   82</a></span>&#160;<span class="keyword">class </span><a class="code" href="classarm__compute_1_1test_1_1datasets_1_1_small4_d_shapes.xhtml">Small4DShapes</a> final : <span class="keyword">public</span> <a class="code" href="classarm__compute_1_1test_1_1framework_1_1dataset_1_1_container_dataset.xhtml">ShapeDataset</a></div>
<div class="line"><a name="l00083"></a><span class="lineno">   83</span>&#160;{</div>
<div class="line"><a name="l00084"></a><span class="lineno">   84</span>&#160;<span class="keyword">public</span>:</div>
<div class="line"><a name="l00085"></a><span class="lineno"><a class="line" href="classarm__compute_1_1test_1_1datasets_1_1_small4_d_shapes.xhtml#a11c11378d206920996fc787494e276fd">   85</a></span>&#160;    <a class="code" href="classarm__compute_1_1test_1_1datasets_1_1_small4_d_shapes.xhtml#a11c11378d206920996fc787494e276fd">Small4DShapes</a>()</div>
<div class="line"><a name="l00086"></a><span class="lineno">   86</span>&#160;        : <a class="code" href="classarm__compute_1_1test_1_1framework_1_1dataset_1_1_container_dataset.xhtml">ShapeDataset</a>(<span class="stringliteral">&quot;Shape&quot;</span>,</div>
<div class="line"><a name="l00087"></a><span class="lineno">   87</span>&#160;    {</div>
<div class="line"><a name="l00088"></a><span class="lineno">   88</span>&#160;        <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>{ 7<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 7<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 5U, 3U },</div>
<div class="line"><a name="l00089"></a><span class="lineno">   89</span>&#160;                     <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>{ 27<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 13<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 37U, 2U },</div>
<div class="line"><a name="l00090"></a><span class="lineno">   90</span>&#160;                     <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>{ 128<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 64<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 21U, 3U }</div>
<div class="line"><a name="l00091"></a><span class="lineno">   91</span>&#160;    })</div>
<div class="line"><a name="l00092"></a><span class="lineno">   92</span>&#160;    {</div>
<div class="line"><a name="l00093"></a><span class="lineno">   93</span>&#160;    }</div>
<div class="line"><a name="l00094"></a><span class="lineno">   94</span>&#160;};</div>
<div class="line"><a name="l00095"></a><span class="lineno">   95</span>&#160;</div>
<div class="line"><a name="l00097"></a><span class="lineno"><a class="line" href="classarm__compute_1_1test_1_1datasets_1_1_small_shapes.xhtml">   97</a></span>&#160;<span class="keyword">class </span><a class="code" href="classarm__compute_1_1test_1_1datasets_1_1_small_shapes.xhtml">SmallShapes</a> final : <span class="keyword">public</span> <a class="code" href="classarm__compute_1_1test_1_1framework_1_1dataset_1_1_container_dataset.xhtml">ShapeDataset</a></div>
<div class="line"><a name="l00098"></a><span class="lineno">   98</span>&#160;{</div>
<div class="line"><a name="l00099"></a><span class="lineno">   99</span>&#160;<span class="keyword">public</span>:</div>
<div class="line"><a name="l00100"></a><span class="lineno"><a class="line" href="classarm__compute_1_1test_1_1datasets_1_1_small_shapes.xhtml#a1b136718b9d6afe5e05c64730fd84531">  100</a></span>&#160;    <a class="code" href="classarm__compute_1_1test_1_1datasets_1_1_small_shapes.xhtml#a1b136718b9d6afe5e05c64730fd84531">SmallShapes</a>()</div>
<div class="line"><a name="l00101"></a><span class="lineno">  101</span>&#160;        : <a class="code" href="classarm__compute_1_1test_1_1framework_1_1dataset_1_1_container_dataset.xhtml">ShapeDataset</a>(<span class="stringliteral">&quot;Shape&quot;</span>,</div>
<div class="line"><a name="l00102"></a><span class="lineno">  102</span>&#160;    {</div>
<div class="line"><a name="l00103"></a><span class="lineno">  103</span>&#160;        <span class="comment">// Batch size 1</span></div>
<div class="line"><a name="l00104"></a><span class="lineno">  104</span>&#160;        <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>{ 9<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 9<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a> },</div>
<div class="line"><a name="l00105"></a><span class="lineno">  105</span>&#160;                     <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>{ 27<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 13<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 2U },</div>
<div class="line"><a name="l00106"></a><span class="lineno">  106</span>&#160;                     <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>{ 128<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 64<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 1U, 3U },</div>
<div class="line"><a name="l00107"></a><span class="lineno">  107</span>&#160;                     <span class="comment">// Batch size 4</span></div>
<div class="line"><a name="l00108"></a><span class="lineno">  108</span>&#160;                     <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>{ 9<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 9<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 3U, 4U },</div>
<div class="line"><a name="l00109"></a><span class="lineno">  109</span>&#160;                     <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>{ 27<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 13<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 2U, 4U },</div>
<div class="line"><a name="l00110"></a><span class="lineno">  110</span>&#160;                     <span class="comment">// Arbitrary batch size</span></div>
<div class="line"><a name="l00111"></a><span class="lineno">  111</span>&#160;                     <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>{ 9<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 9<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 3U, 5U }</div>
<div class="line"><a name="l00112"></a><span class="lineno">  112</span>&#160;    })</div>
<div class="line"><a name="l00113"></a><span class="lineno">  113</span>&#160;    {</div>
<div class="line"><a name="l00114"></a><span class="lineno">  114</span>&#160;    }</div>
<div class="line"><a name="l00115"></a><span class="lineno">  115</span>&#160;};</div>
<div class="line"><a name="l00116"></a><span class="lineno">  116</span>&#160;</div>
<div class="line"><a name="l00118"></a><span class="lineno"><a class="line" href="classarm__compute_1_1test_1_1datasets_1_1_medium_shapes.xhtml">  118</a></span>&#160;<span class="keyword">class </span><a class="code" href="classarm__compute_1_1test_1_1datasets_1_1_medium_shapes.xhtml">MediumShapes</a> final : <span class="keyword">public</span> <a class="code" href="classarm__compute_1_1test_1_1framework_1_1dataset_1_1_container_dataset.xhtml">ShapeDataset</a></div>
<div class="line"><a name="l00119"></a><span class="lineno">  119</span>&#160;{</div>
<div class="line"><a name="l00120"></a><span class="lineno">  120</span>&#160;<span class="keyword">public</span>:</div>
<div class="line"><a name="l00121"></a><span class="lineno"><a class="line" href="classarm__compute_1_1test_1_1datasets_1_1_medium_shapes.xhtml#aa259527d4665a07f78d7512a32fa1bd0">  121</a></span>&#160;    <a class="code" href="classarm__compute_1_1test_1_1datasets_1_1_medium_shapes.xhtml#aa259527d4665a07f78d7512a32fa1bd0">MediumShapes</a>()</div>
<div class="line"><a name="l00122"></a><span class="lineno">  122</span>&#160;        : <a class="code" href="classarm__compute_1_1test_1_1framework_1_1dataset_1_1_container_dataset.xhtml">ShapeDataset</a>(<span class="stringliteral">&quot;Shape&quot;</span>,</div>
<div class="line"><a name="l00123"></a><span class="lineno">  123</span>&#160;    {</div>
<div class="line"><a name="l00124"></a><span class="lineno">  124</span>&#160;        <span class="comment">// Batch size 1</span></div>
<div class="line"><a name="l00125"></a><span class="lineno">  125</span>&#160;        <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>{ 37<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 37<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a> },</div>
<div class="line"><a name="l00126"></a><span class="lineno">  126</span>&#160;                     <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>{ 27<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 33<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 2U },</div>
<div class="line"><a name="l00127"></a><span class="lineno">  127</span>&#160;                     <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>{ 128<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 64<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 1U, 3U },</div>
<div class="line"><a name="l00128"></a><span class="lineno">  128</span>&#160;                     <span class="comment">// Batch size 4</span></div>
<div class="line"><a name="l00129"></a><span class="lineno">  129</span>&#160;                     <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>{ 37<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 37<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 3U, 4U },</div>
<div class="line"><a name="l00130"></a><span class="lineno">  130</span>&#160;                     <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>{ 27<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 33<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 2U, 4U },</div>
<div class="line"><a name="l00131"></a><span class="lineno">  131</span>&#160;                     <span class="comment">// Arbitrary batch size</span></div>
<div class="line"><a name="l00132"></a><span class="lineno">  132</span>&#160;                     <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>{ 37<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 37<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 3U, 5U }</div>
<div class="line"><a name="l00133"></a><span class="lineno">  133</span>&#160;    })</div>
<div class="line"><a name="l00134"></a><span class="lineno">  134</span>&#160;    {</div>
<div class="line"><a name="l00135"></a><span class="lineno">  135</span>&#160;    }</div>
<div class="line"><a name="l00136"></a><span class="lineno">  136</span>&#160;};</div>
<div class="line"><a name="l00137"></a><span class="lineno">  137</span>&#160;</div>
<div class="line"><a name="l00139"></a><span class="lineno"><a class="line" href="classarm__compute_1_1test_1_1datasets_1_1_large_shapes.xhtml">  139</a></span>&#160;<span class="keyword">class </span><a class="code" href="classarm__compute_1_1test_1_1datasets_1_1_large_shapes.xhtml">LargeShapes</a> final : <span class="keyword">public</span> <a class="code" href="classarm__compute_1_1test_1_1framework_1_1dataset_1_1_container_dataset.xhtml">ShapeDataset</a></div>
<div class="line"><a name="l00140"></a><span class="lineno">  140</span>&#160;{</div>
<div class="line"><a name="l00141"></a><span class="lineno">  141</span>&#160;<span class="keyword">public</span>:</div>
<div class="line"><a name="l00142"></a><span class="lineno"><a class="line" href="classarm__compute_1_1test_1_1datasets_1_1_large_shapes.xhtml#a9715c2e5fcad0e230de11c4f66ecf8a3">  142</a></span>&#160;    <a class="code" href="classarm__compute_1_1test_1_1datasets_1_1_large_shapes.xhtml#a9715c2e5fcad0e230de11c4f66ecf8a3">LargeShapes</a>()</div>
<div class="line"><a name="l00143"></a><span class="lineno">  143</span>&#160;        : <a class="code" href="classarm__compute_1_1test_1_1framework_1_1dataset_1_1_container_dataset.xhtml">ShapeDataset</a>(<span class="stringliteral">&quot;Shape&quot;</span>,</div>
<div class="line"><a name="l00144"></a><span class="lineno">  144</span>&#160;    {</div>
<div class="line"><a name="l00145"></a><span class="lineno">  145</span>&#160;        <span class="comment">// Batch size 1</span></div>
<div class="line"><a name="l00146"></a><span class="lineno">  146</span>&#160;        <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>{ 1920<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 1080<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a> },</div>
<div class="line"><a name="l00147"></a><span class="lineno">  147</span>&#160;                     <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>{ 640<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 480<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 2U, 3U },</div>
<div class="line"><a name="l00148"></a><span class="lineno">  148</span>&#160;                     <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>{ 4160<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 3120<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a> },</div>
<div class="line"><a name="l00149"></a><span class="lineno">  149</span>&#160;                     <span class="comment">// Batch size 4</span></div>
<div class="line"><a name="l00150"></a><span class="lineno">  150</span>&#160;                     <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>{ 800<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 600<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 1U, 4U },</div>
<div class="line"><a name="l00151"></a><span class="lineno">  151</span>&#160;    })</div>
<div class="line"><a name="l00152"></a><span class="lineno">  152</span>&#160;    {</div>
<div class="line"><a name="l00153"></a><span class="lineno">  153</span>&#160;    }</div>
<div class="line"><a name="l00154"></a><span class="lineno">  154</span>&#160;};</div>
<div class="line"><a name="l00155"></a><span class="lineno">  155</span>&#160;</div>
<div class="line"><a name="l00157"></a><span class="lineno"><a class="line" href="classarm__compute_1_1test_1_1datasets_1_1_large2_d_shapes.xhtml">  157</a></span>&#160;<span class="keyword">class </span><a class="code" href="classarm__compute_1_1test_1_1datasets_1_1_large2_d_shapes.xhtml">Large2DShapes</a> final : <span class="keyword">public</span> <a class="code" href="classarm__compute_1_1test_1_1framework_1_1dataset_1_1_container_dataset.xhtml">ShapeDataset</a></div>
<div class="line"><a name="l00158"></a><span class="lineno">  158</span>&#160;{</div>
<div class="line"><a name="l00159"></a><span class="lineno">  159</span>&#160;<span class="keyword">public</span>:</div>
<div class="line"><a name="l00160"></a><span class="lineno"><a class="line" href="classarm__compute_1_1test_1_1datasets_1_1_large2_d_shapes.xhtml#aec6e35680c5a27de50d771cc7a4ab568">  160</a></span>&#160;    <a class="code" href="classarm__compute_1_1test_1_1datasets_1_1_large2_d_shapes.xhtml#aec6e35680c5a27de50d771cc7a4ab568">Large2DShapes</a>()</div>
<div class="line"><a name="l00161"></a><span class="lineno">  161</span>&#160;        : <a class="code" href="classarm__compute_1_1test_1_1framework_1_1dataset_1_1_container_dataset.xhtml">ShapeDataset</a>(<span class="stringliteral">&quot;Shape&quot;</span>,</div>
<div class="line"><a name="l00162"></a><span class="lineno">  162</span>&#160;    {</div>
<div class="line"><a name="l00163"></a><span class="lineno">  163</span>&#160;        <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>{ 1920<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 1080<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a> },</div>
<div class="line"><a name="l00164"></a><span class="lineno">  164</span>&#160;                     <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>{ 1245<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 652<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a> },</div>
<div class="line"><a name="l00165"></a><span class="lineno">  165</span>&#160;                     <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>{ 4160<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 3120<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a> }</div>
<div class="line"><a name="l00166"></a><span class="lineno">  166</span>&#160;    })</div>
<div class="line"><a name="l00167"></a><span class="lineno">  167</span>&#160;    {</div>
<div class="line"><a name="l00168"></a><span class="lineno">  168</span>&#160;    }</div>
<div class="line"><a name="l00169"></a><span class="lineno">  169</span>&#160;};</div>
<div class="line"><a name="l00170"></a><span class="lineno">  170</span>&#160;</div>
<div class="line"><a name="l00172"></a><span class="lineno"><a class="line" href="classarm__compute_1_1test_1_1datasets_1_1_large3_d_shapes.xhtml">  172</a></span>&#160;<span class="keyword">class </span><a class="code" href="classarm__compute_1_1test_1_1datasets_1_1_large3_d_shapes.xhtml">Large3DShapes</a> final : <span class="keyword">public</span> <a class="code" href="classarm__compute_1_1test_1_1framework_1_1dataset_1_1_container_dataset.xhtml">ShapeDataset</a></div>
<div class="line"><a name="l00173"></a><span class="lineno">  173</span>&#160;{</div>
<div class="line"><a name="l00174"></a><span class="lineno">  174</span>&#160;<span class="keyword">public</span>:</div>
<div class="line"><a name="l00175"></a><span class="lineno"><a class="line" href="classarm__compute_1_1test_1_1datasets_1_1_large3_d_shapes.xhtml#aa6c076c0bc51f626dc92e460434f39a0">  175</a></span>&#160;    <a class="code" href="classarm__compute_1_1test_1_1datasets_1_1_large3_d_shapes.xhtml#aa6c076c0bc51f626dc92e460434f39a0">Large3DShapes</a>()</div>
<div class="line"><a name="l00176"></a><span class="lineno">  176</span>&#160;        : <a class="code" href="classarm__compute_1_1test_1_1framework_1_1dataset_1_1_container_dataset.xhtml">ShapeDataset</a>(<span class="stringliteral">&quot;Shape&quot;</span>,</div>
<div class="line"><a name="l00177"></a><span class="lineno">  177</span>&#160;    {</div>
<div class="line"><a name="l00178"></a><span class="lineno">  178</span>&#160;        <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>{ 320<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 240<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 3U },</div>
<div class="line"><a name="l00179"></a><span class="lineno">  179</span>&#160;                     <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>{ 383<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 653<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 2U },</div>
<div class="line"><a name="l00180"></a><span class="lineno">  180</span>&#160;                     <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>{ 721<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 123<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 13U }</div>
<div class="line"><a name="l00181"></a><span class="lineno">  181</span>&#160;    })</div>
<div class="line"><a name="l00182"></a><span class="lineno">  182</span>&#160;    {</div>
<div class="line"><a name="l00183"></a><span class="lineno">  183</span>&#160;    }</div>
<div class="line"><a name="l00184"></a><span class="lineno">  184</span>&#160;};</div>
<div class="line"><a name="l00185"></a><span class="lineno">  185</span>&#160;</div>
<div class="line"><a name="l00187"></a><span class="lineno"><a class="line" href="classarm__compute_1_1test_1_1datasets_1_1_large4_d_shapes.xhtml">  187</a></span>&#160;<span class="keyword">class </span><a class="code" href="classarm__compute_1_1test_1_1datasets_1_1_large4_d_shapes.xhtml">Large4DShapes</a> final : <span class="keyword">public</span> <a class="code" href="classarm__compute_1_1test_1_1framework_1_1dataset_1_1_container_dataset.xhtml">ShapeDataset</a></div>
<div class="line"><a name="l00188"></a><span class="lineno">  188</span>&#160;{</div>
<div class="line"><a name="l00189"></a><span class="lineno">  189</span>&#160;<span class="keyword">public</span>:</div>
<div class="line"><a name="l00190"></a><span class="lineno"><a class="line" href="classarm__compute_1_1test_1_1datasets_1_1_large4_d_shapes.xhtml#aeca085a1350713335ede663fcbcfe5f0">  190</a></span>&#160;    <a class="code" href="classarm__compute_1_1test_1_1datasets_1_1_large4_d_shapes.xhtml#aeca085a1350713335ede663fcbcfe5f0">Large4DShapes</a>()</div>
<div class="line"><a name="l00191"></a><span class="lineno">  191</span>&#160;        : <a class="code" href="classarm__compute_1_1test_1_1framework_1_1dataset_1_1_container_dataset.xhtml">ShapeDataset</a>(<span class="stringliteral">&quot;Shape&quot;</span>,</div>
<div class="line"><a name="l00192"></a><span class="lineno">  192</span>&#160;    {</div>
<div class="line"><a name="l00193"></a><span class="lineno">  193</span>&#160;        <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>{ 320<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 123<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 3U, 3U },</div>
<div class="line"><a name="l00194"></a><span class="lineno">  194</span>&#160;                     <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>{ 383<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 413<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 2U, 3U },</div>
<div class="line"><a name="l00195"></a><span class="lineno">  195</span>&#160;                     <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>{ 517<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 123<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 13U, 2U }</div>
<div class="line"><a name="l00196"></a><span class="lineno">  196</span>&#160;    })</div>
<div class="line"><a name="l00197"></a><span class="lineno">  197</span>&#160;    {</div>
<div class="line"><a name="l00198"></a><span class="lineno">  198</span>&#160;    }</div>
<div class="line"><a name="l00199"></a><span class="lineno">  199</span>&#160;};</div>
<div class="line"><a name="l00200"></a><span class="lineno">  200</span>&#160;</div>
<div class="line"><a name="l00202"></a><span class="lineno"><a class="line" href="classarm__compute_1_1test_1_1datasets_1_1_small_direct_convolution_shapes.xhtml">  202</a></span>&#160;<span class="keyword">class </span><a class="code" href="classarm__compute_1_1test_1_1datasets_1_1_small_direct_convolution_shapes.xhtml">SmallDirectConvolutionShapes</a> final : <span class="keyword">public</span> <a class="code" href="classarm__compute_1_1test_1_1framework_1_1dataset_1_1_container_dataset.xhtml">ShapeDataset</a></div>
<div class="line"><a name="l00203"></a><span class="lineno">  203</span>&#160;{</div>
<div class="line"><a name="l00204"></a><span class="lineno">  204</span>&#160;<span class="keyword">public</span>:</div>
<div class="line"><a name="l00205"></a><span class="lineno"><a class="line" href="classarm__compute_1_1test_1_1datasets_1_1_small_direct_convolution_shapes.xhtml#acb0c6c9450dcbca845c4eb86d08e4f5f">  205</a></span>&#160;    <a class="code" href="classarm__compute_1_1test_1_1datasets_1_1_small_direct_convolution_shapes.xhtml#acb0c6c9450dcbca845c4eb86d08e4f5f">SmallDirectConvolutionShapes</a>()</div>
<div class="line"><a name="l00206"></a><span class="lineno">  206</span>&#160;        : <a class="code" href="classarm__compute_1_1test_1_1framework_1_1dataset_1_1_container_dataset.xhtml">ShapeDataset</a>(<span class="stringliteral">&quot;InputShape&quot;</span>,</div>
<div class="line"><a name="l00207"></a><span class="lineno">  207</span>&#160;    {</div>
<div class="line"><a name="l00208"></a><span class="lineno">  208</span>&#160;        <span class="comment">// Batch size 1</span></div>
<div class="line"><a name="l00209"></a><span class="lineno">  209</span>&#160;        <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>{ 35<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 35<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 3U },</div>
<div class="line"><a name="l00210"></a><span class="lineno">  210</span>&#160;                     <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>{ 32<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 37<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 3U },</div>
<div class="line"><a name="l00211"></a><span class="lineno">  211</span>&#160;                     <span class="comment">// Batch size 4</span></div>
<div class="line"><a name="l00212"></a><span class="lineno">  212</span>&#160;                     <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>{ 32<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 37<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 3U, 4U },</div>
<div class="line"><a name="l00213"></a><span class="lineno">  213</span>&#160;                     <span class="comment">// Batch size 8</span></div>
<div class="line"><a name="l00214"></a><span class="lineno">  214</span>&#160;                     <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>{ 32<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 37<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 3U, 8U },</div>
<div class="line"><a name="l00215"></a><span class="lineno">  215</span>&#160;                     <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>{ 33<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 35<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 8U, 8U },</div>
<div class="line"><a name="l00216"></a><span class="lineno">  216</span>&#160;                     <span class="comment">// Arbitrary batch size</span></div>
<div class="line"><a name="l00217"></a><span class="lineno">  217</span>&#160;                     <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>{ 32<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 37<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 3U, 8U }</div>
<div class="line"><a name="l00218"></a><span class="lineno">  218</span>&#160;    })</div>
<div class="line"><a name="l00219"></a><span class="lineno">  219</span>&#160;    {</div>
<div class="line"><a name="l00220"></a><span class="lineno">  220</span>&#160;    }</div>
<div class="line"><a name="l00221"></a><span class="lineno">  221</span>&#160;};</div>
<div class="line"><a name="l00222"></a><span class="lineno">  222</span>&#160;</div>
<div class="line"><a name="l00224"></a><span class="lineno"><a class="line" href="classarm__compute_1_1test_1_1datasets_1_1_depth_concatenate_shapes.xhtml">  224</a></span>&#160;<span class="keyword">class </span><a class="code" href="classarm__compute_1_1test_1_1datasets_1_1_depth_concatenate_shapes.xhtml">DepthConcatenateShapes</a> final : <span class="keyword">public</span> <a class="code" href="classarm__compute_1_1test_1_1framework_1_1dataset_1_1_container_dataset.xhtml">ShapeDataset</a></div>
<div class="line"><a name="l00225"></a><span class="lineno">  225</span>&#160;{</div>
<div class="line"><a name="l00226"></a><span class="lineno">  226</span>&#160;<span class="keyword">public</span>:</div>
<div class="line"><a name="l00227"></a><span class="lineno"><a class="line" href="classarm__compute_1_1test_1_1datasets_1_1_depth_concatenate_shapes.xhtml#a9fa589980f42f44513272bc9ffd2c2e9">  227</a></span>&#160;    <a class="code" href="classarm__compute_1_1test_1_1datasets_1_1_depth_concatenate_shapes.xhtml#a9fa589980f42f44513272bc9ffd2c2e9">DepthConcatenateShapes</a>()</div>
<div class="line"><a name="l00228"></a><span class="lineno">  228</span>&#160;        : <a class="code" href="classarm__compute_1_1test_1_1framework_1_1dataset_1_1_container_dataset.xhtml">ShapeDataset</a>(<span class="stringliteral">&quot;Shape&quot;</span>,</div>
<div class="line"><a name="l00229"></a><span class="lineno">  229</span>&#160;    {</div>
<div class="line"><a name="l00230"></a><span class="lineno">  230</span>&#160;        <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>{ 322<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 243<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a> },</div>
<div class="line"><a name="l00231"></a><span class="lineno">  231</span>&#160;                     <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>{ 463<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 879<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a> },</div>
<div class="line"><a name="l00232"></a><span class="lineno">  232</span>&#160;                     <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>{ 416<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 651<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a> }</div>
<div class="line"><a name="l00233"></a><span class="lineno">  233</span>&#160;    })</div>
<div class="line"><a name="l00234"></a><span class="lineno">  234</span>&#160;    {</div>
<div class="line"><a name="l00235"></a><span class="lineno">  235</span>&#160;    }</div>
<div class="line"><a name="l00236"></a><span class="lineno">  236</span>&#160;};</div>
<div class="line"><a name="l00237"></a><span class="lineno">  237</span>&#160;</div>
<div class="line"><a name="l00239"></a><span class="lineno"><a class="line" href="classarm__compute_1_1test_1_1datasets_1_1_global_pooling_shapes.xhtml">  239</a></span>&#160;<span class="keyword">class </span><a class="code" href="classarm__compute_1_1test_1_1datasets_1_1_global_pooling_shapes.xhtml">GlobalPoolingShapes</a> final : <span class="keyword">public</span> <a class="code" href="classarm__compute_1_1test_1_1framework_1_1dataset_1_1_container_dataset.xhtml">ShapeDataset</a></div>
<div class="line"><a name="l00240"></a><span class="lineno">  240</span>&#160;{</div>
<div class="line"><a name="l00241"></a><span class="lineno">  241</span>&#160;<span class="keyword">public</span>:</div>
<div class="line"><a name="l00242"></a><span class="lineno"><a class="line" href="classarm__compute_1_1test_1_1datasets_1_1_global_pooling_shapes.xhtml#aa2f05979de5779a1ea507dce1b721566">  242</a></span>&#160;    <a class="code" href="classarm__compute_1_1test_1_1datasets_1_1_global_pooling_shapes.xhtml#aa2f05979de5779a1ea507dce1b721566">GlobalPoolingShapes</a>()</div>
<div class="line"><a name="l00243"></a><span class="lineno">  243</span>&#160;        : <a class="code" href="classarm__compute_1_1test_1_1framework_1_1dataset_1_1_container_dataset.xhtml">ShapeDataset</a>(<span class="stringliteral">&quot;Shape&quot;</span>,</div>
<div class="line"><a name="l00244"></a><span class="lineno">  244</span>&#160;    {</div>
<div class="line"><a name="l00245"></a><span class="lineno">  245</span>&#160;        <span class="comment">// Batch size 1</span></div>
<div class="line"><a name="l00246"></a><span class="lineno">  246</span>&#160;        <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>{ 9<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 9<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a> },</div>
<div class="line"><a name="l00247"></a><span class="lineno">  247</span>&#160;                     <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>{ 13<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 13<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 2U },</div>
<div class="line"><a name="l00248"></a><span class="lineno">  248</span>&#160;                     <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>{ 27<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 27<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 1U, 3U },</div>
<div class="line"><a name="l00249"></a><span class="lineno">  249</span>&#160;                     <span class="comment">// Batch size 4</span></div>
<div class="line"><a name="l00250"></a><span class="lineno">  250</span>&#160;                     <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>{ 31<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 31<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 3U, 4U },</div>
<div class="line"><a name="l00251"></a><span class="lineno">  251</span>&#160;                     <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>{ 34<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 34<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 2U, 4U }</div>
<div class="line"><a name="l00252"></a><span class="lineno">  252</span>&#160;    })</div>
<div class="line"><a name="l00253"></a><span class="lineno">  253</span>&#160;    {</div>
<div class="line"><a name="l00254"></a><span class="lineno">  254</span>&#160;    }</div>
<div class="line"><a name="l00255"></a><span class="lineno">  255</span>&#160;};</div>
<div class="line"><a name="l00256"></a><span class="lineno">  256</span>&#160;</div>
<div class="line"><a name="l00257"></a><span class="lineno">  257</span>&#160;} <span class="comment">// namespace datasets</span></div>
<div class="line"><a name="l00258"></a><span class="lineno">  258</span>&#160;} <span class="comment">// namespace test</span></div>
<div class="line"><a name="l00259"></a><span class="lineno">  259</span>&#160;} <span class="comment">// namespace arm_compute</span></div>
<div class="line"><a name="l00260"></a><span class="lineno">  260</span>&#160;<span class="preprocessor">#endif </span><span class="comment">/* __ARM_COMPUTE_TEST_SHAPE_DATASETS_H__ */</span><span class="preprocessor"></span></div>
<div class="ttc" id="classarm__compute_1_1_tensor_shape_xhtml"><div class="ttname"><a href="classarm__compute_1_1_tensor_shape.xhtml">arm_compute::TensorShape</a></div><div class="ttdoc">Shape of a tensor. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_shape_8h_source.xhtml#l00038">TensorShape.h:38</a></div></div>
<div class="ttc" id="classarm__compute_1_1test_1_1datasets_1_1_large_shapes_xhtml"><div class="ttname"><a href="classarm__compute_1_1test_1_1datasets_1_1_large_shapes.xhtml">arm_compute::test::datasets::LargeShapes</a></div><div class="ttdoc">Data set containing large tensor shapes. </div><div class="ttdef"><b>Definition:</b> <a href="_shape_datasets_8h_source.xhtml#l00139">ShapeDatasets.h:139</a></div></div>
<div class="ttc" id="classarm__compute_1_1test_1_1datasets_1_1_global_pooling_shapes_xhtml"><div class="ttname"><a href="classarm__compute_1_1test_1_1datasets_1_1_global_pooling_shapes.xhtml">arm_compute::test::datasets::GlobalPoolingShapes</a></div><div class="ttdoc">Data set containing global pooling tensor shapes. </div><div class="ttdef"><b>Definition:</b> <a href="_shape_datasets_8h_source.xhtml#l00239">ShapeDatasets.h:239</a></div></div>
<div class="ttc" id="classarm__compute_1_1test_1_1datasets_1_1_large2_d_shapes_xhtml"><div class="ttname"><a href="classarm__compute_1_1test_1_1datasets_1_1_large2_d_shapes.xhtml">arm_compute::test::datasets::Large2DShapes</a></div><div class="ttdoc">Data set containing large 2D tensor shapes. </div><div class="ttdef"><b>Definition:</b> <a href="_shape_datasets_8h_source.xhtml#l00157">ShapeDatasets.h:157</a></div></div>
<div class="ttc" id="classarm__compute_1_1test_1_1datasets_1_1_small_shapes_xhtml"><div class="ttname"><a href="classarm__compute_1_1test_1_1datasets_1_1_small_shapes.xhtml">arm_compute::test::datasets::SmallShapes</a></div><div class="ttdoc">Data set containing small tensor shapes. </div><div class="ttdef"><b>Definition:</b> <a href="_shape_datasets_8h_source.xhtml#l00097">ShapeDatasets.h:97</a></div></div>
<div class="ttc" id="classarm__compute_1_1test_1_1datasets_1_1_medium_shapes_xhtml"><div class="ttname"><a href="classarm__compute_1_1test_1_1datasets_1_1_medium_shapes.xhtml">arm_compute::test::datasets::MediumShapes</a></div><div class="ttdoc">Data set containing medium tensor shapes. </div><div class="ttdef"><b>Definition:</b> <a href="_shape_datasets_8h_source.xhtml#l00118">ShapeDatasets.h:118</a></div></div>
<div class="ttc" id="classarm__compute_1_1test_1_1datasets_1_1_large4_d_shapes_xhtml_aeca085a1350713335ede663fcbcfe5f0"><div class="ttname"><a href="classarm__compute_1_1test_1_1datasets_1_1_large4_d_shapes.xhtml#aeca085a1350713335ede663fcbcfe5f0">arm_compute::test::datasets::Large4DShapes::Large4DShapes</a></div><div class="ttdeci">Large4DShapes()</div><div class="ttdef"><b>Definition:</b> <a href="_shape_datasets_8h_source.xhtml#l00190">ShapeDatasets.h:190</a></div></div>
<div class="ttc" id="classarm__compute_1_1test_1_1framework_1_1dataset_1_1_container_dataset_xhtml"><div class="ttname"><a href="classarm__compute_1_1test_1_1framework_1_1dataset_1_1_container_dataset.xhtml">arm_compute::test::framework::dataset::ContainerDataset</a></div><div class="ttdoc">Implementation of a dataset created from a container. </div><div class="ttdef"><b>Definition:</b> <a href="_container_dataset_8h_source.xhtml#l00058">ContainerDataset.h:58</a></div></div>
<div class="ttc" id="classarm__compute_1_1test_1_1datasets_1_1_large3_d_shapes_xhtml_aa6c076c0bc51f626dc92e460434f39a0"><div class="ttname"><a href="classarm__compute_1_1test_1_1datasets_1_1_large3_d_shapes.xhtml#aa6c076c0bc51f626dc92e460434f39a0">arm_compute::test::datasets::Large3DShapes::Large3DShapes</a></div><div class="ttdeci">Large3DShapes()</div><div class="ttdef"><b>Definition:</b> <a href="_shape_datasets_8h_source.xhtml#l00175">ShapeDatasets.h:175</a></div></div>
<div class="ttc" id="classarm__compute_1_1test_1_1datasets_1_1_small4_d_shapes_xhtml_a11c11378d206920996fc787494e276fd"><div class="ttname"><a href="classarm__compute_1_1test_1_1datasets_1_1_small4_d_shapes.xhtml#a11c11378d206920996fc787494e276fd">arm_compute::test::datasets::Small4DShapes::Small4DShapes</a></div><div class="ttdeci">Small4DShapes()</div><div class="ttdef"><b>Definition:</b> <a href="_shape_datasets_8h_source.xhtml#l00085">ShapeDatasets.h:85</a></div></div>
<div class="ttc" id="classarm__compute_1_1test_1_1datasets_1_1_small3_d_shapes_xhtml"><div class="ttname"><a href="classarm__compute_1_1test_1_1datasets_1_1_small3_d_shapes.xhtml">arm_compute::test::datasets::Small3DShapes</a></div><div class="ttdoc">Data set containing small 3D tensor shapes. </div><div class="ttdef"><b>Definition:</b> <a href="_shape_datasets_8h_source.xhtml#l00067">ShapeDatasets.h:67</a></div></div>
<div class="ttc" id="classarm__compute_1_1test_1_1datasets_1_1_large3_d_shapes_xhtml"><div class="ttname"><a href="classarm__compute_1_1test_1_1datasets_1_1_large3_d_shapes.xhtml">arm_compute::test::datasets::Large3DShapes</a></div><div class="ttdoc">Data set containing large 3D tensor shapes. </div><div class="ttdef"><b>Definition:</b> <a href="_shape_datasets_8h_source.xhtml#l00172">ShapeDatasets.h:172</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml_a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb"><div class="ttname"><a href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">arm_compute::Channel::U</a></div><div class="ttdoc">Cb/U channel. </div></div>
<div class="ttc" id="_datasets_8h_xhtml"><div class="ttname"><a href="_datasets_8h.xhtml">Datasets.h</a></div></div>
<div class="ttc" id="classarm__compute_1_1test_1_1datasets_1_1_depth_concatenate_shapes_xhtml_a9fa589980f42f44513272bc9ffd2c2e9"><div class="ttname"><a href="classarm__compute_1_1test_1_1datasets_1_1_depth_concatenate_shapes.xhtml#a9fa589980f42f44513272bc9ffd2c2e9">arm_compute::test::datasets::DepthConcatenateShapes::DepthConcatenateShapes</a></div><div class="ttdeci">DepthConcatenateShapes()</div><div class="ttdef"><b>Definition:</b> <a href="_shape_datasets_8h_source.xhtml#l00227">ShapeDatasets.h:227</a></div></div>
<div class="ttc" id="classarm__compute_1_1test_1_1datasets_1_1_small2_d_shapes_xhtml_af5e1a4f2a8c5ec30856fbe4f3efe4ee9"><div class="ttname"><a href="classarm__compute_1_1test_1_1datasets_1_1_small2_d_shapes.xhtml#af5e1a4f2a8c5ec30856fbe4f3efe4ee9">arm_compute::test::datasets::Small2DShapes::Small2DShapes</a></div><div class="ttdeci">Small2DShapes()</div><div class="ttdef"><b>Definition:</b> <a href="_shape_datasets_8h_source.xhtml#l00055">ShapeDatasets.h:55</a></div></div>
<div class="ttc" id="classarm__compute_1_1test_1_1datasets_1_1_large2_d_shapes_xhtml_aec6e35680c5a27de50d771cc7a4ab568"><div class="ttname"><a href="classarm__compute_1_1test_1_1datasets_1_1_large2_d_shapes.xhtml#aec6e35680c5a27de50d771cc7a4ab568">arm_compute::test::datasets::Large2DShapes::Large2DShapes</a></div><div class="ttdeci">Large2DShapes()</div><div class="ttdef"><b>Definition:</b> <a href="_shape_datasets_8h_source.xhtml#l00160">ShapeDatasets.h:160</a></div></div>
<div class="ttc" id="classarm__compute_1_1test_1_1datasets_1_1_small_direct_convolution_shapes_xhtml"><div class="ttname"><a href="classarm__compute_1_1test_1_1datasets_1_1_small_direct_convolution_shapes.xhtml">arm_compute::test::datasets::SmallDirectConvolutionShapes</a></div><div class="ttdoc">Data set containing small tensor shapes for direct convolution. </div><div class="ttdef"><b>Definition:</b> <a href="_shape_datasets_8h_source.xhtml#l00202">ShapeDatasets.h:202</a></div></div>
<div class="ttc" id="classarm__compute_1_1test_1_1datasets_1_1_small_shapes_xhtml_a1b136718b9d6afe5e05c64730fd84531"><div class="ttname"><a href="classarm__compute_1_1test_1_1datasets_1_1_small_shapes.xhtml#a1b136718b9d6afe5e05c64730fd84531">arm_compute::test::datasets::SmallShapes::SmallShapes</a></div><div class="ttdeci">SmallShapes()</div><div class="ttdef"><b>Definition:</b> <a href="_shape_datasets_8h_source.xhtml#l00100">ShapeDatasets.h:100</a></div></div>
<div class="ttc" id="classarm__compute_1_1test_1_1datasets_1_1_global_pooling_shapes_xhtml_aa2f05979de5779a1ea507dce1b721566"><div class="ttname"><a href="classarm__compute_1_1test_1_1datasets_1_1_global_pooling_shapes.xhtml#aa2f05979de5779a1ea507dce1b721566">arm_compute::test::datasets::GlobalPoolingShapes::GlobalPoolingShapes</a></div><div class="ttdeci">GlobalPoolingShapes()</div><div class="ttdef"><b>Definition:</b> <a href="_shape_datasets_8h_source.xhtml#l00242">ShapeDatasets.h:242</a></div></div>
<div class="ttc" id="classarm__compute_1_1test_1_1datasets_1_1_small1_d_shape_xhtml_a42e48f27686347e905050153e3e87dc5"><div class="ttname"><a href="classarm__compute_1_1test_1_1datasets_1_1_small1_d_shape.xhtml#a42e48f27686347e905050153e3e87dc5">arm_compute::test::datasets::Small1DShape::Small1DShape</a></div><div class="ttdeci">Small1DShape()</div><div class="ttdef"><b>Definition:</b> <a href="_shape_datasets_8h_source.xhtml#l00042">ShapeDatasets.h:42</a></div></div>
<div class="ttc" id="classarm__compute_1_1test_1_1datasets_1_1_small2_d_shapes_xhtml"><div class="ttname"><a href="classarm__compute_1_1test_1_1datasets_1_1_small2_d_shapes.xhtml">arm_compute::test::datasets::Small2DShapes</a></div><div class="ttdoc">Data set containing small 2D tensor shapes. </div><div class="ttdef"><b>Definition:</b> <a href="_shape_datasets_8h_source.xhtml#l00052">ShapeDatasets.h:52</a></div></div>
<div class="ttc" id="classarm__compute_1_1test_1_1framework_1_1dataset_1_1_singleton_dataset_xhtml"><div class="ttname"><a href="classarm__compute_1_1test_1_1framework_1_1dataset_1_1_singleton_dataset.xhtml">arm_compute::test::framework::dataset::SingletonDataset</a></div><div class="ttdoc">Implementation of a dataset holding a single value. </div><div class="ttdef"><b>Definition:</b> <a href="_singleton_dataset_8h_source.xhtml#l00046">SingletonDataset.h:46</a></div></div>
<div class="ttc" id="classarm__compute_1_1test_1_1datasets_1_1_medium_shapes_xhtml_aa259527d4665a07f78d7512a32fa1bd0"><div class="ttname"><a href="classarm__compute_1_1test_1_1datasets_1_1_medium_shapes.xhtml#aa259527d4665a07f78d7512a32fa1bd0">arm_compute::test::datasets::MediumShapes::MediumShapes</a></div><div class="ttdeci">MediumShapes()</div><div class="ttdef"><b>Definition:</b> <a href="_shape_datasets_8h_source.xhtml#l00121">ShapeDatasets.h:121</a></div></div>
<div class="ttc" id="classarm__compute_1_1test_1_1datasets_1_1_small4_d_shapes_xhtml"><div class="ttname"><a href="classarm__compute_1_1test_1_1datasets_1_1_small4_d_shapes.xhtml">arm_compute::test::datasets::Small4DShapes</a></div><div class="ttdoc">Data set containing small 4D tensor shapes. </div><div class="ttdef"><b>Definition:</b> <a href="_shape_datasets_8h_source.xhtml#l00082">ShapeDatasets.h:82</a></div></div>
<div class="ttc" id="classarm__compute_1_1test_1_1datasets_1_1_large4_d_shapes_xhtml"><div class="ttname"><a href="classarm__compute_1_1test_1_1datasets_1_1_large4_d_shapes.xhtml">arm_compute::test::datasets::Large4DShapes</a></div><div class="ttdoc">Data set containing large 4D tensor shapes. </div><div class="ttdef"><b>Definition:</b> <a href="_shape_datasets_8h_source.xhtml#l00187">ShapeDatasets.h:187</a></div></div>
<div class="ttc" id="classarm__compute_1_1test_1_1datasets_1_1_small3_d_shapes_xhtml_a231cfeceb3e607c02a8347adeb894eb9"><div class="ttname"><a href="classarm__compute_1_1test_1_1datasets_1_1_small3_d_shapes.xhtml#a231cfeceb3e607c02a8347adeb894eb9">arm_compute::test::datasets::Small3DShapes::Small3DShapes</a></div><div class="ttdeci">Small3DShapes()</div><div class="ttdef"><b>Definition:</b> <a href="_shape_datasets_8h_source.xhtml#l00070">ShapeDatasets.h:70</a></div></div>
<div class="ttc" id="classarm__compute_1_1test_1_1framework_1_1dataset_1_1_singleton_dataset_xhtml_ad23d34842f593ae646353d39fc0466cd"><div class="ttname"><a href="classarm__compute_1_1test_1_1framework_1_1dataset_1_1_singleton_dataset.xhtml#ad23d34842f593ae646353d39fc0466cd">arm_compute::test::framework::dataset::SingletonDataset&lt; TensorShape &gt;::SingletonDataset</a></div><div class="ttdeci">SingletonDataset(std::string name, TensorShape &amp;&amp;value)</div><div class="ttdoc">Construct dataset with given name and value. </div><div class="ttdef"><b>Definition:</b> <a href="_singleton_dataset_8h_source.xhtml#l00054">SingletonDataset.h:54</a></div></div>
<div class="ttc" id="classarm__compute_1_1test_1_1datasets_1_1_depth_concatenate_shapes_xhtml"><div class="ttname"><a href="classarm__compute_1_1test_1_1datasets_1_1_depth_concatenate_shapes.xhtml">arm_compute::test::datasets::DepthConcatenateShapes</a></div><div class="ttdoc">Data set containing 2D tensor shapes for DepthConcatenate. </div><div class="ttdef"><b>Definition:</b> <a href="_shape_datasets_8h_source.xhtml#l00224">ShapeDatasets.h:224</a></div></div>
<div class="ttc" id="classarm__compute_1_1test_1_1datasets_1_1_large_shapes_xhtml_a9715c2e5fcad0e230de11c4f66ecf8a3"><div class="ttname"><a href="classarm__compute_1_1test_1_1datasets_1_1_large_shapes.xhtml#a9715c2e5fcad0e230de11c4f66ecf8a3">arm_compute::test::datasets::LargeShapes::LargeShapes</a></div><div class="ttdeci">LargeShapes()</div><div class="ttdef"><b>Definition:</b> <a href="_shape_datasets_8h_source.xhtml#l00142">ShapeDatasets.h:142</a></div></div>
<div class="ttc" id="_tensor_shape_8h_xhtml"><div class="ttname"><a href="_tensor_shape_8h.xhtml">TensorShape.h</a></div></div>
<div class="ttc" id="classarm__compute_1_1test_1_1datasets_1_1_small1_d_shape_xhtml"><div class="ttname"><a href="classarm__compute_1_1test_1_1datasets_1_1_small1_d_shape.xhtml">arm_compute::test::datasets::Small1DShape</a></div><div class="ttdoc">Data set containing 1D tensor shapes. </div><div class="ttdef"><b>Definition:</b> <a href="_shape_datasets_8h_source.xhtml#l00039">ShapeDatasets.h:39</a></div></div>
<div class="ttc" id="classarm__compute_1_1test_1_1datasets_1_1_small_direct_convolution_shapes_xhtml_acb0c6c9450dcbca845c4eb86d08e4f5f"><div class="ttname"><a href="classarm__compute_1_1test_1_1datasets_1_1_small_direct_convolution_shapes.xhtml#acb0c6c9450dcbca845c4eb86d08e4f5f">arm_compute::test::datasets::SmallDirectConvolutionShapes::SmallDirectConvolutionShapes</a></div><div class="ttdeci">SmallDirectConvolutionShapes()</div><div class="ttdef"><b>Definition:</b> <a href="_shape_datasets_8h_source.xhtml#l00205">ShapeDatasets.h:205</a></div></div>
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